Search: onr:"swepub:oai:research.chalmers.se:d4ec0125-bd15-4806-8746-aabf6742b123" >
Bytecode-Based Mult...
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Bollina, SrujanaUniversity of South Carolina
(author)
Bytecode-Based Multiple Condition Coverage: An Initial Investigation
- Article/chapterEnglish2020
Publisher, publication year, extent ...
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2020-09-30
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Cham :Springer International Publishing,2020
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electronicrdacarrier
Numbers
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LIBRIS-ID:oai:research.chalmers.se:d4ec0125-bd15-4806-8746-aabf6742b123
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https://doi.org/10.1007/978-3-030-59762-7_16DOI
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https://research.chalmers.se/publication/520881URI
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https://research.chalmers.se/publication/522609URI
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https://gup.ub.gu.se/publication/298726URI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:kon swepub-publicationtype
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Subject category:ref swepub-contenttype
Notes
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Masking occurs when one condition prevents another from influencing the output of a Boolean expression. Adequacy criteria such as Multiple Condition Coverage (MCC) overcome masking within one expression, but offer no guarantees about subsequent expressions. As a result, a Boolean expression written as a single complex statement will yield more effective test cases than when written as a series of simple expressions. Many approaches to automated test case generation for Java operate not on the source code, but on bytecode. The transformation to bytecode simplifies complex expressions into multiple expressions, introducing masking. We propose Bytecode-MCC, a new adequacy criterion designed to group bytecode expressions and reformulate them into complex expressions. Bytecode-MCC should produce test obligations that are more likely to reveal faults in program logic than tests covering the simplified bytecode. A preliminary study shows potential improvements from attaining Bytecode-MCC coverage. However, Bytecode-MCC is difficult to optimize, and means of increasing coverage are needed before the technique can make a difference in practice. We propose potential methods to improve coverage.
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Gay, Gregory,1987Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU)(Swepub:gu)xgagre
(author)
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University of South CarolinaInstitutionen för data- och informationsteknik (GU)
(creator_code:org_t)
Related titles
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In:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Cham : Springer International PublishingSSBSE 2020, s. 220-2361611-33490302-97439783030597627
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